Microgrid intelligent operation and maintenance controller and method

Abstract

The invention discloses a micro-grid intelligent operation and maintenance controller and method, and relates to the technical field of micro-grid operation and maintenance. The intelligent operation and maintenance subsystem is formed by interactively connecting a plurality of cluster servers, each cluster server adopts a small convolutional neural network to establish a fault information set corresponding to each front-end device, and the cluster servers are utilized to train and learn a convolutional neural network model so as to obtain a small convolutional neural network and a large convolutional neural network; therefore, the state data set is identified so as to judge whether fault information exists or not. The micro-grid intelligent operation and maintenance controller and the micro-grid intelligent operation and maintenance method have good openness and compatibility, can be suitable for various micro-grids composed of different primary devices, can automatically judge micro-grid faults and carry out corresponding fault processing under the unattended condition, improve the micro-grid fault processing efficiency and reduce the fault processing cost. The dependence of micro-grid operation on operation and maintenance personnel is reduced, and the operation stability of the micro-grid is improved.

Description

Technical Field

[0001] The present invention relates to the field of microgrid operation and maintenance technology, and in particular to a microgrid intelligent operation and maintenance controller and method. Background Art

[0002] Microgrid is a power generation solution. The power source of microgrid is small photovoltaic, small wind power and energy storage. The transmission network is low voltage. It is a small power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc.; it is an autonomous system that can achieve self-control, protection and management. It can be connected to the external power grid or operate in isolation.

[0003] The development and extension of microgrids can fully promote the large-scale access of distributed power sources and renewable energy, realize highly reliable supply of multiple energy forms to loads, is an effective way to realize active distribution networks, and is a transition from traditional power grids to smart grids.

[0004] With the development trend of science and technology Internet, the development direction of various control systems is getting closer and closer to intelligent control, using intelligent modes to automatically perform daily operation and maintenance tasks, reducing manual intervention, and improving the efficiency of operation and maintenance through intelligent monitoring and analysis functions. At the same time, it reduces operation and maintenance costs, and can predict system load changes, plan and adjust resources in advance, and ensure high performance and stability of the system.

[0005] The intelligent operation and maintenance control system is an operation and maintenance management platform that combines advanced technologies such as artificial intelligence and big data analysis. Its main purpose is to improve the efficiency and stability of operation and maintenance work through intelligent monitoring and analysis functions, while reducing operation and maintenance costs. This system can automatically perform daily operation and maintenance tasks, reduce manual intervention, and predict system load changes, plan and adjust resources in advance, and ensure high performance and stability of the system; for example, in the automated operation and maintenance stage, based on pre-defined rules, through real-time resource and application performance collection and calculation, when certain rules are met, the corresponding repeatable operation and maintenance script is automatically triggered. On this basis, intelligent operation and maintenance further uses artificial intelligence to solve problems that automated operation and maintenance cannot solve, such as complex fault diagnosis and performance optimization tasks.

[0006] Although microgrids are small in size, they involve multiple technical sub-fields of the power system, and have high requirements on the knowledge system and work skills of operation and maintenance personnel. In addition, according to the scope of application of microgrids, the operating environment is relatively harsh, and sufficient resident personnel are required to monitor and maintain them, resulting in high personnel costs when using microgrids. Therefore, it is extremely necessary to develop an intelligent operation and maintenance technology based on the use of microgrids. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a microgrid intelligent operation and maintenance controller and method, which solves the problems raised in the above background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a microgrid intelligent operation and maintenance controller, including an intelligent operation and maintenance subsystem;

[0009] The intelligent operation and maintenance subsystem consists of multiple cluster servers that are interactively connected. The cluster server uses a small convolutional neural network to establish a set of fault information corresponding to each front-end device. The cluster server is used to train and learn the convolutional neural network model to obtain a small convolutional neural network and a large convolutional neural network, so as to identify the state data set to determine whether there is fault information.

[0010] The intelligent operation and maintenance subsystem includes database establishment module, microgrid monitoring and data acquisition module, data analysis and mining module, fault prediction and diagnosis module, automatic operation and maintenance decision and execution module, and user feedback and learning module;

[0011] The database establishment module includes abnormal power grid status, power grid system logs, performance indicators, and event records;

[0012] The microgrid monitoring and data acquisition module uses multiple sensor devices to monitor the microgrid operation process, collect abnormal instructions, and perform data collection operations on its operating environment according to the settings of the sensors, realizing command control while expanding the data database;

[0013] The microgrid monitoring and data acquisition module also includes a data storage and management unit, which uses cloud service technology for data storage to process large-scale data. The data storage and management unit is used to monitor the system operation status in real time, and its monitoring scope covers hardware equipment and software systems. Through data collection, abnormal conditions of the system can be discovered in time, providing real-time data support for subsequent analysis and decision-making;

[0014] Data analysis and mining module: The collected data needs to be deeply analyzed and mined. Machine learning algorithms are used to classify, cluster, and analyze the association of data to identify patterns and trends in the data. By analyzing historical data, a model for the normal operation of the system is established. When real-time data deviates from the normal model, it is determined that there are potential problems in the system.

[0015] The fault prediction and diagnosis module consists of a fault prediction module and a fault identification module. Based on the results of data analysis and mining, it predicts system faults and makes accurate diagnoses. Based on the pre-established fault model, it issues early warnings and notifies operation and maintenance personnel to take corresponding measures.

[0016] The automatic operation and maintenance decision-making and execution module predicts the fault or diagnoses the root cause of the problem, makes operation and maintenance decisions and performs corresponding operations according to pre-set operation and maintenance rules and strategies.

[0017] Optionally, the power grid system log is used to record system operation instructions and events, including user login and program operation error information;

[0018] The grid performance indicators include grid voltage and grid current, which are used to reflect the operating status of the system, including CPU usage and memory occupancy;

[0019] The event log contains abnormal conditions that occur during the operation of the microgrid, and serves as a comparison database backup cache to provide comparison material for subsequent analysis and decision-making.

[0020] Optionally, the microgrid monitoring and data acquisition module further includes a communication model configuration unit and an alarm information push unit;

[0021] in,

[0022] The communication model configuration unit is used to configure the communication information model of the microgrid controller, forming a communication channel between the primary and secondary devices of the microgrid, the microgrid controller and the information collection and recording unit; the alarm information push unit is used to send alarm information to the fault judgment module and the remote management module when the operating status of the microgrid changes. The alarm information includes the details of the equipment whose operating status has changed and its operating status information.

[0023] Optionally, the data analysis and mining module also includes a system analysis and decision-making unit, which obtains the source state of the microgrid based on the microgrid state change information and the fault judgment results, selects the destination state of the microgrid based on the principle of maximizing the power supply range, and selects matching fault handling measures from the microgrid strategy table based on the microgrid source state and the destination state.

[0024] Optionally, the fault determination module includes a fault state determination unit, a fault component identification unit and a determination result push unit;

[0025] After receiving the alarm information, it is determined whether there is a fault in the microgrid based on the collected operating status information and the preset fault status information; when a fault occurs, the faulty component of the microgrid is located based on the status based on incomplete information, and the fault judgment result is generated, and the judgment result content is sent to the automatic operation and maintenance decision and execution module.

[0026] Optionally, the automatic operation and maintenance decision specifically includes:

[0027] Microgrid control system script repair, automatically executing repair scripts based on microgrid fault data analysis results;

[0028] Microgrid automatic repair and fault self-healing, using automatic repair, grid control system restart, equipment change, to achieve intelligent fault response mechanism;

[0029] Sensor information security management: security monitoring of sensors in microgrid operation, automatic identification and response to security threats;

[0030] Optimize resource allocation and rationally allocate resources based on the historical data and current trends of the microgrid system to ensure effective resource utilization and cost control.

[0031] Optionally, the user feedback and learning module is composed of a user feedback unit, a diagnostic report generating unit, and a system learning improvement unit;

[0032] User feedback unit, which provides an intuitive user interface and microgrid fault reports, and enables the microgrid operation and maintenance team to monitor system status and trends and make timely adjustments and optimizations;

[0033] Diagnostic report generation unit: microgrid users set the generation time node by themselves, based on 24 hours, to diagnose the cluster regularly and generate diagnostic reports;

[0034] The system learning improvement unit regularly evaluates and optimizes the fault diagnosis and operation and maintenance information generated during the operation of the microgrid.

[0035] A method for intelligent operation and maintenance control of a microgrid as claimed in any one of the above claims, comprising the following specific steps:

[0036] Step 1: Establish a corresponding data foundation for the use environment and applicable fields of the microgrid; collect and organize the data generated during the operation and maintenance of the microgrid, and establish a corresponding data database based on the collected data;

[0037] Step 2: Improve the data quality while establishing the data database, clean and pre-process the collected data, remove invalid data, duplicate data and erroneous data, identify and correct outliers in the server performance data during the collection process, and conduct a secondary review. After the review is completed, integrate the power grid data into multiple data sets using time series analysis methods;

[0038] Step 3: Use the operation and maintenance system to integrate the microgrid monitoring sensors with the operation and maintenance system. When the system is monitored to be abnormal, the automated operation and maintenance operation is triggered.

[0039] Step 4: Monitor sensor data and collect real-time data from sensor components, including microgrid servers, operation and maintenance system network equipment, operation and maintenance applications, and microgrid operation and maintenance log files. By monitoring microgrid data, the entire operation and maintenance control information can be obtained, and potential problems can be analyzed and handled accordingly.

[0040] Step 5: By collecting real-time abnormal data and comparing it with the data database, the abnormal state of the microgrid is judged regularly, and the root cause of the fault is maintained and solved according to the abnormal state and the marked fault end. The microgrid controller is used to operate switches and switches through the communication channel, adjust the working mode and operating parameters of the microgrid related equipment, and return the execution operation results;

[0041] Step 6: Check and calibrate the marked fixed information segment again to determine whether it meets the operation standards;

[0042] If the operating indicators are met, the microgrid is started and monitored in real time through the operation and maintenance controller;

[0043] If the operating indicators are not met, repeat steps 3 to 5 until the operating indicators are met.

[0044] Optionally, the specific steps of the automated operation and maintenance operation in step 3 are as follows:

[0045] (1) Mark the abnormal data according to the sensor data, and extend the mark in the reverse direction of the mark point until the initial end of the abnormal state of the mark value, and extract the data set involved to establish a temporary data packet;

[0046] (2) Using a small convolutional neural network to establish a fault information set corresponding to each front-end device, processing the status information set according to a preset deep learning algorithm, and using a large convolutional neural network to identify the status information set based on the fault information set; determining whether there is fault information in the status information set;

[0047] (3) If there is fault information, a deep learning algorithm is used to analyze massive amounts of log data to quickly locate the root cause of the fault.

[0048] The present invention provides a microgrid intelligent operation and maintenance controller and method, which has the following beneficial effects:

[0049] The microgrid intelligent operation and maintenance controller and method can automatically identify faulty components, generate and execute fault handling control operations when the microgrid operating state changes, thereby autonomously and intelligently completing the microgrid operation and maintenance control operations, and realizing the functions of restoring power supply, isolating faults, automatically switching operating modes and strategies, automatically maintaining batteries, and remotely managing microgrids after failures without human supervision.

[0050] in,

[0051] This system can monitor various performance indicators of servers, network equipment, application software, etc. in real time, such as processor utilization, memory occupancy, etc., to help users monitor the system's operating status in real time. Secondly, the system can capture and display the device's alarm information in real time to ensure that users can discover and deal with potential problems as soon as possible, ensure that users can receive alarm information in time and take corresponding measures, and support automated troubleshooting and recovery functions to improve troubleshooting and recovery efficiency and quality, improve operation and maintenance efficiency, reduce operation and maintenance costs, optimize resource utilization, and reduce manual operation errors through automated task execution. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a schematic diagram of the components of the controller in the invention;

[0053] Figure 2 It is a schematic diagram of the process flow in the invention. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0055] In the description of the present invention, unless otherwise specified, "plurality" means two or more than two; the orientations or positional relationships indicated by the terms "upper", "lower", "left", "right", "inner", "outer", "front end", "rear end", "head", "tail", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0056] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0057] See also Figure 1 , a microgrid intelligent operation and maintenance controller, including an intelligent operation and maintenance subsystem;

[0058] The intelligent operation and maintenance subsystem consists of multiple cluster servers that are interactively connected. The cluster server uses a small convolutional neural network to establish a set of fault information corresponding to each front-end device. The cluster server is used to train and learn the convolutional neural network model to obtain a small convolutional neural network and a large convolutional neural network, so as to identify the state data set to determine whether there is fault information.

[0059] The intelligent operation and maintenance subsystem includes database establishment module, microgrid monitoring and data acquisition module, data analysis and mining module, fault prediction and diagnosis module, automatic operation and maintenance decision and execution module, and user feedback and learning module;

[0060] The database establishment module includes abnormal power grid status, power grid system logs, performance indicators, and event records;

[0061] The power grid system log is used to record the system's operating instructions and events, including user login and program operation error information;

[0062] The grid performance indicators include grid voltage and grid current, which are used to reflect the operating status of the system, including CPU usage and memory occupancy;

[0063] The event record contains the abnormal conditions that occurred during the operation of the microgrid, which serves as a comparison database backup cache and provides comparison materials for subsequent analysis and decision-making;

[0064] The microgrid monitoring and data acquisition module uses multiple sensor devices to monitor the microgrid operation process, collect abnormal instructions, and perform data collection operations on its operating environment according to the settings of the sensors, realizing command control while expanding the data database;

[0065] The microgrid monitoring and data acquisition module also includes a communication model configuration unit and an alarm information push unit;

[0066] in,

[0067] The communication model configuration unit is used to configure the communication information model of the microgrid controller, and form a communication channel between the primary and secondary devices of the microgrid, the microgrid controller and the information collection and recording unit; the alarm information push unit is used to send alarm information to the fault identification module and the remote management module when the operating state of the microgrid changes. The alarm information includes the details of the equipment whose operating state has changed and its operating state information;

[0068] The microgrid monitoring and data acquisition module also includes a data storage and management unit, which uses cloud service technology for data storage to process large-scale data. The data storage and management unit is used to monitor the system operation status in real time. The monitoring scope covers hardware equipment (such as servers, network equipment, etc.) and software systems (such as operating systems, applications, etc.); through data collection, abnormal conditions of the system can be discovered in time, providing real-time data support for subsequent analysis and decision-making;

[0069] Data analysis and mining module: The collected data needs to be deeply analyzed and mined. Machine learning algorithms are used to classify, cluster, and analyze the association of data to identify patterns and trends in the data. By analyzing historical data, a model for the normal operation of the system is established. When real-time data deviates from the normal model, it is determined that there are potential problems in the system.

[0070] The data analysis and mining module also includes a system analysis and decision-making unit, which obtains the source state of the microgrid based on the microgrid state change information and fault identification results, selects the destination state of the microgrid based on the principle of maximizing the power supply range, and selects matching fault handling measures from the microgrid strategy table based on the source state and destination state of the microgrid;

[0071] The fault prediction and diagnosis module consists of a fault prediction module and a fault identification module. Based on the results of data analysis and mining, it predicts system faults and makes accurate diagnoses. Based on the pre-established fault model, it issues early warnings and notifies operation and maintenance personnel to take corresponding measures.

[0072] The fault discrimination module includes a fault state discrimination unit, a fault component identification unit and a discrimination result push unit;

[0073] After receiving the alarm information, determine whether the microgrid has a fault based on the collected operating status information and the preset fault status information; when a fault occurs, locate the microgrid fault component based on the status based on incomplete information, generate a fault judgment result, and send the judgment result content to the automatic operation and maintenance decision and execution module;

[0074] The automatic operation and maintenance decision-making and execution module predicts the fault or diagnoses the root cause of the problem, makes operation and maintenance decisions and executes corresponding operations according to the pre-set operation and maintenance rules and strategies;

[0075] Automatic operation and maintenance decisions include:

[0076] Microgrid control system script repair, automatically executing repair scripts based on microgrid fault data analysis results;

[0077] Microgrid automatic repair and fault self-healing, using automatic repair, grid control system restart, equipment change, to achieve intelligent fault response mechanism;

[0078] Sensor information security management: security monitoring of sensors in microgrid operation, automatic identification and response to security threats;

[0079] Optimize resource allocation and rationally allocate resources based on historical data and current trends of the microgrid system to ensure effective use of resources and cost control;

[0080] The user feedback and learning module consists of a user feedback unit, a diagnostic report generation unit, and a system learning improvement unit;

[0081] User feedback unit, which provides an intuitive user interface and microgrid fault reports, and enables the microgrid operation and maintenance team to monitor system status and trends and make timely adjustments and optimizations;

[0082] Diagnostic report generation unit: microgrid users set the generation time node by themselves, based on 24 hours, to diagnose the cluster regularly and generate diagnostic reports;

[0083] The system learning improvement unit regularly evaluates and optimizes the fault diagnosis and operation and maintenance information generated during the operation of the microgrid.

[0084] See also Figure 2 , a method for intelligent operation and maintenance control of a microgrid, comprising the following specific steps:

[0085] Step 1: Establish a corresponding data foundation for the use environment and applicable fields of the microgrid; collect and organize the data generated during the operation and maintenance of the microgrid, and establish a corresponding data database based on the collected data;

[0086] Step 2: Improve the data quality while establishing the data database, clean and pre-process the collected data, remove invalid data, duplicate data and erroneous data, identify and correct outliers in the server performance data during the collection process, and conduct a secondary review. After the review is completed, integrate the power grid data into multiple data sets using time series analysis methods;

[0087] Step 3: Use the operation and maintenance system to integrate the microgrid monitoring sensors with the operation and maintenance system. When the system is monitored to be abnormal, the automated operation and maintenance operation is triggered.

[0088] The specific steps of automated operation and maintenance are as follows:

[0089] (1) Mark the abnormal data according to the sensor data, and extend the mark in the reverse direction of the mark point until the initial end of the abnormal state of the mark value, and extract the data set involved to establish a temporary data packet;

[0090] (2) Using a small convolutional neural network to establish a fault information set corresponding to each front-end device, processing the status information set according to a preset deep learning algorithm, and using a large convolutional neural network to identify the status information set based on the fault information set; determining whether there is fault information in the status information set;

[0091] (3) If there is fault information, use deep learning algorithms to analyze massive amounts of log data to quickly locate the root cause of the fault;

[0092] Step 4: Monitor sensor data and collect real-time data from sensor components, including microgrid servers, operation and maintenance system network equipment, operation and maintenance applications, and microgrid operation and maintenance log files. By monitoring microgrid data, the entire operation and maintenance control information can be obtained, and potential problems can be analyzed and handled accordingly.

[0093] Step 5: By collecting real-time abnormal data and comparing it with the data database, the abnormal state of the microgrid is judged regularly, and the root cause of the fault is maintained and solved according to the abnormal state and the marked fault end. The microgrid controller is used to operate switches and circuit breakers through the communication channel, adjust the working mode and operating parameters of microgrid-related equipment, and return the execution operation results.

[0094] Step 6: Check and calibrate the marked fixed information segment again to determine whether it meets the operation standards;

[0095] If the operating indicators are met, the microgrid is started and monitored in real time through the operation and maintenance controller;

[0096] If the operating indicators are not met, repeat steps 3 to 5 until the operating indicators are met.

[0097] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A microgrid intelligent operation and maintenance controller, characterized in that: Including intelligent operation and maintenance subsystem; The intelligent operation and maintenance subsystem consists of multiple cluster servers that are interactively connected. The cluster server uses a small convolutional neural network to establish a set of fault information corresponding to each front-end device. The cluster server is used to train and learn the convolutional neural network model to obtain a small convolutional neural network and a large convolutional neural network, so as to identify the state data set to determine whether there is fault information. The intelligent operation and maintenance subsystem includes database establishment module, microgrid monitoring and data acquisition module, data analysis and mining module, fault prediction and diagnosis module, automatic operation and maintenance decision and execution module, and user feedback and learning module; The database establishment module includes abnormal power grid status, power grid system logs, performance indicators, and event records; The microgrid monitoring and data acquisition module uses multiple sensor devices to monitor the microgrid operation process, collect abnormal instructions, and perform data collection operations on its operating environment according to the settings of the sensors, realizing command control while expanding the data database; The microgrid monitoring and data acquisition module also includes a data storage and management unit, which uses cloud service technology for data storage to process large-scale data. The data storage and management unit is used to monitor the system operation status in real time, and its monitoring scope covers hardware equipment and software systems. Through data collection, abnormal conditions of the system can be discovered in time, providing real-time data support for subsequent analysis and decision-making; Data analysis and mining module: The collected data needs to be deeply analyzed and mined. Machine learning algorithms are used to classify, cluster, and analyze the association of data to identify patterns and trends in the data. By analyzing historical data, a model for the normal operation of the system is established. When real-time data deviates from the normal model, it is determined that there are potential problems in the system. The fault prediction and diagnosis module consists of a fault prediction module and a fault identification module. Based on the results of data analysis and mining, it predicts system faults and makes accurate diagnoses. Based on the pre-established fault model, it issues early warnings and notifies operation and maintenance personnel to take corresponding measures. The automatic operation and maintenance decision-making and execution module predicts the fault or diagnoses the root cause of the problem, makes operation and maintenance decisions and performs corresponding operations according to pre-set operation and maintenance rules and strategies.

2. A microgrid intelligent operation and maintenance controller according to claim 1, characterized in that: The power grid system log is used to record the system's operating instructions and events, including user login and program operation error information; The grid performance indicators include grid voltage and grid current, which are used to reflect the operating status of the system, including CPU usage and memory occupancy; The event log contains abnormal conditions that occur during the operation of the microgrid, and serves as a comparison database backup cache to provide comparison material for subsequent analysis and decision-making.

3. A microgrid intelligent operation and maintenance controller according to claim 1, characterized in that: The microgrid monitoring and data acquisition module also includes a communication model configuration unit and an alarm information push unit; in, The communication model configuration unit is used to configure the communication information model of the microgrid controller, forming a communication channel between the primary and secondary devices of the microgrid, the microgrid controller and the information collection and recording unit; the alarm information push unit is used to send alarm information to the fault judgment module and the remote management module when the operating status of the microgrid changes. The alarm information includes the details of the equipment whose operating status has changed and its operating status information.

4. A microgrid intelligent operation and maintenance controller according to claim 1, characterized in that: The data analysis and mining module also includes a system analysis and decision-making unit, which obtains the microgrid source state according to the microgrid state change information and the fault judgment result, selects the microgrid destination state according to the principle of maximizing the power supply range, and selects matching fault handling measures from the microgrid strategy table according to the microgrid source state and the destination state.

5. A microgrid intelligent operation and maintenance controller according to claim 1, characterized in that: The fault determination module includes a fault state determination unit, a fault component identification unit and a determination result push unit; After receiving the alarm information, determine whether the microgrid has a fault based on the collected operating status information and the preset fault status information; and When a fault occurs, the faulty component of the microgrid is located according to the state based on incomplete information, a fault identification result is generated, and the identification result content is sent to the automatic operation and maintenance decision and execution module.

6. A microgrid intelligent operation and maintenance controller according to claim 1, characterized in that: The automatic operation and maintenance decision specifically includes: Microgrid control system script repair, automatically executing repair scripts based on microgrid fault data analysis results; Microgrid automatic repair and fault self-healing, using automatic repair, grid control system restart, equipment change, to achieve intelligent fault response mechanism; Sensor information security management: security monitoring of sensors in microgrid operation, automatic identification and response to security threats; Optimize resource allocation and rationally allocate resources based on the historical data and current trends of the microgrid system to ensure effective resource utilization and cost control.

7. A microgrid intelligent operation and maintenance controller according to claim 1, characterized in that: The user feedback and learning module consists of a user feedback unit, a diagnostic report generation unit, and a system learning improvement unit; User feedback unit, which provides an intuitive user interface and microgrid fault reports, and enables the microgrid operation and maintenance team to monitor system status and trends and make timely adjustments and optimizations; Diagnostic report generation unit: microgrid users set the generation time node by themselves, based on 24 hours, to diagnose the cluster regularly and generate diagnostic reports; The system learning improvement unit regularly evaluates and optimizes the fault diagnosis and operation and maintenance information generated during the operation of the microgrid.

8. A method for intelligent operation and maintenance control of a microgrid as claimed in any one of claims 1 to 7, characterized in that: The specific steps include: Step 1: Establish a corresponding data foundation for the use environment and applicable fields of the microgrid; collect and organize the data generated during the operation and maintenance of the microgrid, and establish a corresponding data database based on the collected data; Step 2: Improve the data quality while establishing the data database, clean and pre-process the collected data, remove invalid data, duplicate data and erroneous data, identify and correct outliers in the server performance data during the collection process, and conduct a secondary review. After the review is completed, integrate the power grid data into multiple data sets using time series analysis methods; Step 3: Use the operation and maintenance system to integrate the microgrid monitoring sensors with the operation and maintenance system. When the system is monitored to be abnormal, the automated operation and maintenance operation is triggered. Step 4: Monitor sensor data and collect real-time data from sensor components, including microgrid servers, operation and maintenance system network equipment, operation and maintenance applications, and microgrid operation and maintenance log files. By monitoring microgrid data, the entire operation and maintenance control information can be obtained, and potential problems can be analyzed and handled accordingly. Step 5: By collecting real-time abnormal data and comparing it with the data database, the abnormal state of the microgrid is judged regularly, and the root cause of the fault is maintained and solved according to the abnormal state and the marked fault end. The microgrid controller is used to operate switches and switches through the communication channel, adjust the working mode and operating parameters of the microgrid related equipment, and return the execution operation results; Step 6: Check and calibrate the marked fixed information segment again to determine whether it meets the operation standards; If the operating indicators are met, the microgrid is started and monitored in real time through the operation and maintenance controller; If the operating indicators are not met, repeat steps 3 to 5 until the operating indicators are met.

9. A method for intelligent operation and maintenance control of a microgrid according to claim 8, characterized in that: The specific steps of the automated operation and maintenance operation in step 3 are as follows: (1) Mark the abnormal data according to the sensor data, and extend the mark in the reverse direction of the mark point until the initial end of the abnormal state of the mark value, and extract the data set involved to establish a temporary data packet; (2) A small convolutional neural network is used to establish a fault information set corresponding to each front-end device, the status information set is processed according to a preset deep learning algorithm, and a large convolutional neural network is used to identify the status information set based on the fault information set; Determine whether there is fault information in the state information set; (3) If there is fault information, a deep learning algorithm is used to analyze massive amounts of log data to quickly locate the root cause of the fault.

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